Yangsibo Huang

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 41

Top Topics

Data Representations

Top Venues

IEEE Trans. Medical Imaging

Publications

Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal
AI Risk Management Should Incorporate Both Safety and Security. CoRR (2024)
Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson
Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR (2024)
Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Daogao Liu, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
Mind the Privacy Unit! User-Level Differential Privacy for Language Model Fine-Tuning. CoRR (2024)
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Chiyuan Zhang
LabelDP-Pro: Learning with Label Differential Privacy via Projections. ICLR (2024)
Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation. ICLR (2024)
Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson
A Safe Harbor for AI Evaluation and Red Teaming. CoRR (2024)
Tinghao Xie, Xiangyu Qi, Yi Zeng, Yangsibo Huang, Udari Madhushani Sehwag, Kaixuan Huang, Luxi He, Boyi Wei, Dacheng Li, Ying Sheng, Ruoxi Jia, Bo Li, Kai Li, Danqi Chen, Peter Henderson, Prateek Mittal
SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors. CoRR (2024)
Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang
Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models. CoRR (2024)
Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson
Evaluating Copyright Takedown Methods for Language Models. CoRR (2024)
Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang
MUSE: Machine Unlearning Six-Way Evaluation for Language Models. CoRR (2024)
Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie, Xiangyu Qi, Mengzhou Xia, Prateek Mittal, Mengdi Wang, Peter Henderson
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications. CoRR (2024)
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer
Detecting Pretraining Data from Large Language Models. ICLR (2024)
Yangsibo Huang, Samyak Gupta, Zexuan Zhong, Kai Li, Danqi Chen
Privacy Implications of Retrieval-Based Language Models. EMNLP (2023)
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
Sparsity-Preserving Differentially Private Training of Large Embedding Models. NeurIPS (2023)
Yangsibo Huang, Chun-Yin Huang, Xiaoxiao Li, Kai Li
A Dataset Auditing Method for Collaboratively Trained Machine Learning Models. IEEE Trans. Medical Imaging 42 (7) (2023)
Yangsibo Huang, Samyak Gupta, Zexuan Zhong, Kai Li, Danqi Chen
Privacy Implications of Retrieval-Based Language Models. CoRR (2023)
Yangsibo Huang, Daogao Liu, Zexuan Zhong, Weijia Shi, Yin Tat Lee
kNN-Adapter: Efficient Domain Adaptation for Black-Box Language Models. CoRR (2023)
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer
Detecting Pretraining Data from Large Language Models. CoRR (2023)
Jiaxi Yang, Wenglong Deng, Benlin Liu, Yangsibo Huang, Xiaoxiao Li
Matching-based Data Valuation for Generative Model. CoRR (2023)
Yangsibo Huang, Samyak Gupta, Mengzhou Xia, Kai Li, Danqi Chen
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation. CoRR (2023)
Yangsibo Huang, Haotian Jiang, Daogao Liu, Mohammad Mahdian, Jieming Mao, Vahab Mirrokni
Learning across Data Owners with Joint Differential Privacy. CoRR (2023)
Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, Nicolas Papernot, Ryan Rogers, Milan Shen, Shuang Song, Weijie J. Su, Andreas Terzis, Abhradeep Thakurta, Sergei Vassilvitskii, Yu-Xiang Wang, Li Xiong, Sergey Yekhanin, Da Yu, Huanyu Zhang, Wanrong Zhang
Challenges towards the Next Frontier in Privacy. CoRR (2023)
Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang
Sparsity-Preserving Differentially Private Training of Large Embedding Models. CoRR (2023)
Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen
Recovering Private Text in Federated Learning of Language Models. CoRR (2022)
Samyak Gupta, Yangsibo Huang, Zexuan Zhong, Tianyu Gao, Kai Li, Danqi Chen
Recovering Private Text in Federated Learning of Language Models. NeurIPS (2022)
Yangsibo Huang, Xiaoxiao Li, Kai Li
EMA: Auditing Data Removal from Trained Models. MICCAI (5) (2021)
Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. NeurIPS (2021)
Yangsibo Huang, Samyak Gupta, Zhao Song, Kai Li, Sanjeev Arora
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning. CoRR (2021)
Yangsibo Huang, Xiaoxiao Li, Kai Li
EMA: Auditing Data Removal from Trained Models. CoRR (2021)
Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora
InstaHide: Instance-hiding Schemes for Private Distributed Learning. CoRR (2020)
Xiaoxiao Li, Yangsibo Huang, Binghui Peng, Zhao Song, Kai Li
MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery. CoRR (2020)
Yangsibo Huang, Yushan Su, Sachin Ravi, Zhao Song, Sanjeev Arora, Kai Li
Privacy-preserving Learning via Deep Net Pruning. CoRR (2020)
Wei Qiu, Yangsibo Huang, Quanzheng Li
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks. CoRR (2020)
Ziheng Duan, Daniel Montes, Yangsibo Huang, Dufan Wu, Javier M. Romero, Ramon Gilberto Gonzalez, Quanzheng Li
Deep Learning Based Detection and Localization of Cerebal Aneurysms in Computed Tomography Angiography. CoRR (2020)
Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora
TextHide: Tackling Data Privacy in Language Understanding Tasks. CoRR (2020)
Yangsibo Huang, Zhao Song, Kai Li, Sanjeev Arora
InstaHide: Instance-hiding Schemes for Private Distributed Learning. ICML (2020)
Wei Qiu, Yangsibo Huang, Quanzheng Li
IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks. IEEE BigData (2020)
Yangsibo Huang, Zhao Song, Danqi Chen, Kai Li, Sanjeev Arora
TextHide: Tackling Data Privacy for Language Understanding Tasks. EMNLP (Findings) (2020)
Ryan Neph, Yangsibo Huang, Youming Yang, Ke Sheng
DeepMCDose: A Deep Learning Method for Efficient Monte Carlo Beamlet Dose Calculation by Predictive Denoising in MR-Guided Radiotherapy. AIRT@MICCAI (2019)
Yunze Man, Yangsibo Huang, Junyi Feng, Xi Li, Fei Wu
Deep Q Learning Driven CT Pancreas Segmentation With Geometry-Aware U-Net. IEEE Trans. Medical Imaging 38 (8) (2019)
Yunze Man, Yangsibo Huang, Junyi Feng, Xi Li, Fei Wu
Deep Q Learning Driven CT Pancreas Segmentation with Geometry-Aware U-Net. CoRR (2019)